Technology Category
Philosophy and Ethics of AI: Bias, Fairness & EquityNatural Language Processing: Ethics — Bias, Fairness, Transparency & PrivacyMachine Learning: Ethics, Bias, and Fairness
A Bridge to Nowhere: A Healthcare Case Study for Non-Reformist Design
🤖 AI Summary
This paper critically examines the limitations of U.S. healthcare prior authorization automation reforms: while ostensibly aimed at reducing administrative burden and treatment delays, current federal interventions reinforce insurers’ structural power. Employing critical case analysis and normative framework development, the study advances a “non-reformist” technological intervention—rejecting optimization of extractive systems in favor of a novel techno-ethical paradigm grounded in design justice, feminist refusal practices, and abolitionist theory. It articulates four guiding principles for ethically grounded, anti-extractive digital health governance. The analysis reveals the inherently conservative character of automation reforms, arguing that public digital governance must move beyond system maintenance toward dismantling insurance power, disrupting data exploitation, and enabling patient sovereignty. The work contributes original theoretical frameworks and actionable policy pathways for health informatics and public technology governance. (149 words)
Technology Category
Application Category
📝 Abstract
In the face of intensified datafication and automation in public sector industries, frameworks like design justice and the feminist practice of refusal provide help to identify and mitigate structural harm and challenge inequities reproduced in digitized infrastructures. This paper applies those frameworks to emerging efforts across the U.S. healthcare industry to automate prior authorization -- a process whereby insurance companies determine whether a treatment or service is 'medically necessary' before agreeing to cover it. Federal regulatory interventions turn to datafication and automation to reduce the harms of this widely unpopular process shown to delay vital treatments and create immense administrative burden for healthcare providers and patients. This paper explores emerging prior authorization reforms as a case study, applying the frameworks of design justice and refusal to highlight the inherent conservatism of interventions oriented towards improving the user experience of extractive systems. I further explore how the abolitionist framework of non-reformist reform helps to clarify alternative interventions that would mitigate the harms of prior authorization in ways that do not reproduce or extend the power of insurance companies. I propose a set of four tenets for nonreformist design to mitigate structural harms and advance design justice in a broad set of domains.
Problem
Research questions and friction points this paper is trying to address.
Address structural harm in healthcare automation.
Challenge inequities in prior authorization processes.
Propose non-reformist design to mitigate insurance power.
Innovation
Methods, ideas, or system contributions that make the work stand out.
Applies design justice and feminist refusal frameworks
Analyzes prior authorization automation in healthcare
Proposes nonreformist design tenets to mitigate harms
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